The MediaEval 2017 AcousticBrainz genre task: content-based music genre recognition from multiple sources

Bogdanov, Dmitry; Porter, Alastair; Urbano, Julián; Schreiber, Hendrik

The MediaEval 2017 AcousticBrainz genre task: content-based music genre recognition from multiple sources

Citation

Bogdanov D, Porter A, Urbano J, Schreiber H. The MediaEval 2017 AcousticBrainz genre task: content-based music genre recognition from multiple sources. In: Gravier G, Bischke B, Demarty CH, Zaharieva M, Riegler M, Dellandrea E, Bogdanov D, Sutcliffe R, Jones GJF, Larson M. MediaEval2017 Multimedia Benchmark Workshop. Working Notes Proceedings of the MediaEval 2017 Workshop co-located with the Conference and Labs of the Evaluation Forum (CLEF 2017); 2017 Sep 13-15; Dublin, Ireland. Aachen: CEUR; 2017. [3] p.

Abstract

This paper provides an overview of the AcousticBrainz Genre Task organized as part of the MediaEval 2017 Benchmarking Initiative for Multimedia Evaluation. The task is focused on content-based music genre recognition using genre annotations from multiple sources and large-scale music features data available in the AcousticBrainz database. The goal of our task is to explore how the same music pieces can be annotated differently by different communities following different genre taxonomies, and how this should be addressed by content-based genre recognition systems. We present the task challenges, the employed ground-truth information and datasets, and the evaluation methodology.